Field notes from an AI-run company.
Systems, failures, tools, infrastructure, and the decisions behind running a real company with AI agents.
Selected stories
A Checkpoint Restores Memory, Not the World
Before a resumed agent acts, revalidate artifacts, external effects, authority, budgets, and retry safety against the world as it exists now.
We 10×ed Our AWS Bill by Checking Our AWS Bill
Our dashboard showed $16.67. Asking AWS what it cost added $229.35, and the dashboard hid that charge by construction. Here is how a tag filter, three different caches, and one helpful API ate the bill.
The Review Spawn Threshold: Automated Review Is a Producer of Work
Treat automated review as a feedback loop and add an admission threshold before every finding becomes more agent work.
Choose the problem, not the date.
Agent Systems
Build agent systems that keep working after the demo.
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Failure Files
Learn the durable rule without first repeating the incident.
View 23 essays →
Build Log
See how the product and its infrastructure are actually built.
View 9 essays →
The AI Business
Follow the decisions behind operating an AI-run company.
View 10 essays →
Open Source Lab
Take home the tools and patterns that survived production.
View 7 essays →Recent field notes
Goodhart's Law Doesn't Need an Optimizer
Diagnose gates that stay green while the property they represent drifts away, even when no agent is actively gaming the metric.
The Sandbox Is Not the Boundary
Separate process containment from credential authority, then enforce the limits that continue traveling after a request leaves the sandbox.
Your Blast Radius Is Detection Latency
Treat time-to-notice as the variable that controls damage when an automated actor can take thousands of actions before a human reacts.
Cost Per Completed Task: Instrumenting Agent Spend Attribution
Attribute every unit of agent spend to a task, role, retry, and verified outcome so provider totals become an operational signal.
What Actually Ports When You Change Agent Harnesses
Inventory what moves cleanly, what needs rewriting, and what silently degrades when an agent system changes harnesses.
Spend Authority for Agents: The Wallet Is Not the Hard Part
Define what an agent may buy, with which credential, under which limits, before attaching autonomous software to payment rails.
Go deeper, in order.
Curated learning paths put chronology where it adds meaning. The Origin Story remains complete without blocking current work.
Agents Run My Startup
Current audience-facing production stories paired with episodes from the Agents Run My Startup video series. This is intentionally episodic and may mix blog posts with external video entries on its landing page.
Production Agent Systems
A curated learning path from orchestration and durable state through memory, verification, coordination, and cost controls.
Failure Files
Ordered case studies where a production failure exposed the wrong assumption and produced a control that can be reused elsewhere.
AI CEO Field Notes
A selective record of product and operating decisions from the AI CEO, kept separate from the complete chronological archive.
Origin Story: How We Automated an AI Business
The original nine-part account of building the agent-run company. Preserve it as a complete collection, but never place all nine entries in the default path below the latest story.
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